Learning Bimanual Laparoscopic Appendectomy Without Robot-Collected Demonstr
Overview
This research presents an end-to-end pipeline for training a surgical robot policy using motion data captured from standard laparoscopic instruments. The system uses inertial, time-of-flight, and Hall sensors to track instrument state without external cameras. A diffusion policy is trained on both ex-vivo and in-vivo demonstrations, achieving appendectomy in three of four live rabbits. The robot serves as a timing reference and executor, with no demonstration collection.
From arXiv Robotics — research abstracts
Event evidence and corrections
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Reported quantity · live rabbits: 4 other · Basis not reported
“tions we train a diffusion policy with a fine-tuned DINOv3 backbone, selecting its design by closed-loop rollouts in a physics simulator reconstructed from depth maps of an ex-vivo rabbit appendix. The policy is then retrained on 849 in-vivo demonstrations from four live rabbits and deployed on four additional live rabbits with electrosurgery armed. With the surgeon selecting the surgical phase, the policy completed”
Exact source · revision 1Source owner not reported
Reported quantity · additional live rabbits: 4 other · Basis not reported
“tions we train a diffusion policy with a fine-tuned DINOv3 backbone, selecting its design by closed-loop rollouts in a physics simulator reconstructed from depth maps of an ex-vivo rabbit appendix. The policy is then retrained on 849 in-vivo demonstrations from four live rabbits and deployed on four additional live rabbits with electrosurgery armed. With the surgeon selecting the surgical phase, the policy completed”
Exact source · revision 1Source owner not reported
Evidence dependency changes (3)
- 2026-10-30T21:57:04.294Z · evidence updated · source revision 1. Evidence extraction was updated; current source attributions are shown above.
- 2026-10-30T21:56:58.753Z · evidence updated · source revision 1. Evidence extraction was updated; current source attributions are shown above.
- 2026-10-22T09:20:37.192Z · evidence updated · source revision 1. Evidence extraction was updated; current source attributions are shown above.
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- arXiv Robotics — research abstractsSignalFrom Instrument-Mounted Demonstrations to In-Vivo Execution: Learning Bimanual Laparoscopic Appendectomy Without Robot-Collected Demonstrations
This research presents an end-to-end pipeline for training a surgical robot policy using motion data captured from standard laparoscopic instruments. The system uses inertial, time-of-flight, and Hall sensors to track instrument state without external cameras. A diffusion policy is trained on both ex-vivo and in-vivo demonstrations, achieving appendectomy in three of four live rabbits. The robot serves as a timing reference and executor, with no demonstration collection.
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